Computer Science Researcher

Overview

The applicant who is selected for this position will be part of a team of engineers and researchers conducting research and development (R&D) activities focused on accelerating the development and deployment of real-world test methodology to evaluate communications protocols in Uncrewed Aircraft Systems (UAS) for first responder solutions.

Work Location is Physically at NIST (Boulder, CO).

Qualifications

• A Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field
• Knowledge of network communications, network routing, and radio signaling
• Knowledge of robotics, UAS, or autonomous software programming (PX4, ArduPilot, AirSim, MAVLink)
• Knowledge of software engineering for virtual simulation applications
• Experience with modern AI tools and applications (AWS, GCP, Azure, MLFlow, SQL, BigQuery, Snowflake)
• Experience with development and manipulation of software code, such as Python, C, C++, Qt, JavaScript
• Knowledge of data structures, formats, and software coding curation processes
• Experience with developing open-source code, identifying use cases, and evaluating dataset quality and representativeness
• Knowledge of mathematical probability and statistics, and optimization methods
• Knowledge of machine learning, including supervised and unsupervised learning, deep learning, and model evaluation
• Knowledge of dataset biases and labeling issues
• Knowledge of translating operational needs into solvable radio signal or networking problems

Research Proposal

Key responsibilities will include, but are not limited to:

• Conduct a literature review and document criteria for drone communications simulator solutions and the datasets that are used to train and test them.
• Prepare industry landscape identifying long-range communications, mesh networking, and best practices on developing methodologies of communications technologies.
• Develop a software program for a new drone communications simulator platform or to retrofit an existing platform, integrating radio hardware communications components.
• Develop open-source code and processes.
• Create and collect measurement data for the drone simulator.
• Document the dataset curation process for public use and determine the target public safety datasets and dataset enhancement options.
• Participate in public safety working groups and stakeholder testing to compare simulations with live UAS flights and curate shared information from collaborators.
• Evaluate drone simulator use cases and what datasets could be used to train and test them, as well as identify technology challenges and gaps to address.